The Challenge
United operates the world’s 3rd-largest 737 fleet (330 aircraft, plus 100 MAX on order). Tire changes had been the #1 delay driver for on-time departures for over 4 years. Capital-intensive engineering fixes weren’t the answer - newly available AI/LLM tools opened the door to a data-driven approach instead.
Our Approach
I visited 6+ airports to meet with site leaders and off-shift shop personnel to understand real process challenges. We mapped the full process - parts, tooling, staging, handoffs, technician sequence - and identified repeatable failure patterns: parts not staged, inconsistent tooling, documentation and scheduling gaps.
We analyzed 3 years of service delay data to isolate root causes and station-level performance, focusing resources on the three worst-performing stations.
3 Worst-Performing Stations
3 Best-Performing Stations
The Outcome
The new process didn’t just fix the three worst-performing stations - it became the standard. Results have held steady and continued to scale across the network.
14% YoY Reduction
Departure delays from tire changes, year over year
3 Worst → 3 Best
Turned the three worst-performing stations into the three best-performing
$9.7M Annual Value
From improved on-time departures, with the standardized process now replicated across major hubs
